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README.md ADDED
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+ ---
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+ library_name: peft
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+ license: other
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+ base_model: mistralai/Ministral-8B-Instruct-2410
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+ tags:
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+ - llama-factory
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+ - generated_from_trainer
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+ model-index:
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+ - name: Ministral-8B-Instruct-2410-PsyCourse-info-chain-fold2
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # Ministral-8B-Instruct-2410-PsyCourse-info-chain-fold2
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+
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+ This model is a fine-tuned version of [mistralai/Ministral-8B-Instruct-2410](https://huggingface.co/mistralai/Ministral-8B-Instruct-2410) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0910
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.0001
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+ - train_batch_size: 1
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+ - eval_batch_size: 1
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+ - seed: 42
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+ - gradient_accumulation_steps: 16
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+ - total_train_batch_size: 16
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+ - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: cosine
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+ - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 5.0
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:------:|:----:|:---------------:|
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+ | 0.2166 | 0.3951 | 10 | 0.1788 |
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+ | 0.0962 | 0.7901 | 20 | 0.1047 |
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+ | 0.0934 | 1.1852 | 30 | 0.0954 |
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+ | 0.0552 | 1.5802 | 40 | 0.0880 |
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+ | 0.0958 | 1.9753 | 50 | 0.0805 |
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+ | 0.0305 | 2.3704 | 60 | 0.0868 |
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+ | 0.0531 | 2.7654 | 70 | 0.0816 |
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+ | 0.0233 | 3.1605 | 80 | 0.0808 |
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+ | 0.0213 | 3.5556 | 90 | 0.0854 |
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+ | 0.0341 | 3.9506 | 100 | 0.0898 |
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+ | 0.0174 | 4.3457 | 110 | 0.0914 |
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+ | 0.027 | 4.7407 | 120 | 0.0910 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.12.0
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+ - Transformers 4.46.1
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+ - Pytorch 2.5.1+cu124
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+ - Datasets 3.1.0
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+ - Tokenizers 0.20.3
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